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Updated: Aug 27, 2025

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

Published on: January 13, 2016

Host Gene Expression to Predict Sepsis Progression.

Cassandra Fiorino¹, Yiling Liu¹, Ricardo Henao^1,2

¹Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC.

Critical Care Medicine

|September 30, 2022

Summary

This summary is machine-generated.

Host gene expression cannot reliably predict sepsis progression using the Sepsis-3 category. However, transcriptomic signatures showed potential for predicting ICU admission or death, though not with sufficient accuracy for clinical use.

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Area of Science:

Genomics
Computational Biology
Infectious Disease

Background:

Sepsis leads to significant mortality, often without clear signs of severe infection.
Host gene expression changes precede clinical manifestation of illness.
Early intervention is crucial but hampered by delayed diagnosis.

Purpose of the Study:

Develop transcriptomic models to predict sepsis or shock progression within 72 hours.
Validate existing transcriptomic signatures for predicting 28-day mortality.

Main Methods:

Retrospective analysis of RNA sequencing data from 277 patients with infection.
Utilized Least Absolute Shrinkage and Selection Operator (LASSO) modeling.
Evaluated four previously identified gene signatures for mortality prediction.

Main Results:

No significant gene expression differences were found when sepsis progression was defined by Sepsis-3 category increase.
1,178 differentially expressed genes were identified when progression was defined by ICU admission or 28-day mortality.
A model based on these genes predicted progression (AUC 0.71); validated signatures predicted mortality (AUC 0.70-0.75).

Conclusions:

The Sepsis-3 category is not suitable for transcriptomic prediction of sepsis progression.
Transcriptomic signatures showed differential response for ICU admission or death prediction.
Existing signatures lack sufficient accuracy for clinical utility in predicting 28-day sepsis mortality.